PROJECT SUMMARY/ABSTRACT Many leading causes of death have declined significantly over the past 100 years (e.g., tuberculosis, pneumonia/influenza, gastritis); however, the suicide rate is virtually identical to what it was 100 years ago. Lack of progress in the prevention of suicide is due in large part to the limited understanding of this problem. Suicidal thoughts and behaviors (STBs), like other behavior problems (e.g., alcohol use, substance use, eating disorders), rarely occur in the research lab where they can be carefully probed and cannot be ethically induced in the lab. As a result, experts lack a firm understanding of the fundamental properties of STBs, and of how, why, and when they unfold in nature. The purpose of this study is to address this enormous gap by using newly developed smartphone and wearable biosensor technologies to conduct an intensive longitudinal study that will advance the understanding and prediction of STBs and related behaviors. This study will monitor 600 people (300 adults and 300 adolescents) at elevated risk of STBs (i.e., those presenting to a psychiatric hospital with suicide ideation and/or a recent suicide attempt) during a high risk time period (i.e., post-hospitalization). The first aim of this study is to identify digital phenotypes of STBs using data collected both actively/subjectively using repeated smartphone surveys and passively/objectively using continuous data from smartphones (e.g., GPS, accelerometer, communications data) and wearable biosensors (e.g., electrodermal activity, accelerometer). The second aim is to map the dynamic trajectories of STBs over time. The third aim is to identify short-term predictors of STBs during the 6 months post- hospital discharge. Ongoing research by the proposed team demonstrates the feasibility of: recruiting and retaining the proposed samples, intensively monitoring them over time using digital devices, and using analyses of these rich data streams to make discoveries about how STBs and related behaviors unfold in nature. The data collected in this study will provide a rich data source that will be used by our research team and collaborative researchers to advance the understanding, prediction, and ultimate prevention of STBs and related outcomes.